fix bug

mesh_reconstruction/recon.py

@@ -12,8 +12,8 @@ from scripts.utils import to_py3d_mesh, init_target
 def reconstruct_stage1(pils: List[Image.Image], steps=100, vertices=None, faces=None, start_edge_len=0.15, end_edge_len=0.005, decay=0.995, return_mesh=True, loss_expansion_weight=0.1, gain=0.1):
     vertices, faces = vertices.to("cuda"), faces.to("cuda")
     assert len(pils) == 4
-    mv,proj = make_star_cameras_orthographic(4, 1)
-    renderer = Pytorch3DNormalsRenderer(mv,proj,list(pils[0].size))
+    mv,proj = make_star_cameras_orthographic_py3d([0, 270, 180, 90], device="cuda", focal=1., dist=4.0)
+    renderer = Pytorch3DNormalsRenderer(cameras, list(pils[0].size), device="cuda")
     
     target_images = init_target(pils, new_bkgd=(0., 0., 0.)) # 4s
     # 1. no rotate

mesh_reconstruction/refine.py

@@ -17,8 +17,8 @@ def run_mesh_refine(vertices, faces, pils: List[Image.Image], steps=100, start_e
     poission_steps = []
 
     assert len(pils) == 4
-    mv,proj = make_star_cameras_orthographic(4, 1)          
-    renderer = Pytorch3DNormalsRenderer(mv,proj,list(pils[0].size))
+    mv,proj = make_star_cameras_orthographic_py3d([0, 270, 180, 90], device="cuda", focal=1., dist=4.0)     
+    renderer = Pytorch3DNormalsRenderer(cameras, list(pils[0].size), device="cuda")
 
     target_images = init_target(pils, new_bkgd=(0., 0., 0.)) # 4s
     # 1. no rotate

scripts/multiview_inference.py

@@ -92,7 +92,10 @@ def geo_reconstruct(rgb_pils, normal_pils, front_pil, do_refine=False, predict_n
         vertices, faces = reconstruct_stage1(normal_stg1, steps=200, vertices=vertices, faces=faces, start_edge_len=0.1, end_edge_len=0.02, gain=0.05, return_mesh=False, loss_expansion_weight=expansion_weight)
     elif init_type in ["ball"]:
         vertices, faces = reconstruct_stage1(normal_stg1, steps=200, end_edge_len=0.01, return_mesh=False, loss_expansion_weight=expansion_weight)
-    vertices, faces = run_mesh_refine(vertices, faces, rm_normals, steps=100, start_edge_len=0.02, end_edge_len=0.005, decay=0.99, update_normal_interval=20, update_warmup=5, return_mesh=False, process_inputs=False, process_outputs=False)
+    
+    normal_stg2 = [img.resize((1024, 1024)) for img in rm_normals]  # reduce computation on huggingface demo, use 1024 instead of 2048
+
+    vertices, faces = run_mesh_refine(vertices, faces, normal_stg2, steps=100, start_edge_len=0.02, end_edge_len=0.005, decay=0.99, update_normal_interval=20, update_warmup=5, return_mesh=False, process_inputs=False, process_outputs=False)
     meshes = simple_clean_mesh(to_pyml_mesh(vertices, faces), apply_smooth=True, stepsmoothnum=1, apply_sub_divide=True, sub_divide_threshold=0.25).to("cuda")
     new_meshes = multiview_color_projection(meshes, img_list, resolution=1024, device="cuda", complete_unseen=True, confidence_threshold=0.2, cameras_list = get_cameras_list([0, 90, 180, 270], "cuda", focal=1))
     return new_meshes